fig1

Container-surface-guided dual-task learning for defect detection in complex port scenes

Figure 1. Overall architecture of the proposed container-surface-prior-guided dual-task network. The shared backbone and neck extract multi-scale features, while the detection and segmentation branches are connected through MG-CTI for lightweight bidirectional task interaction. The photographs in the upper-left input and lower-right detection-output panels were acquired at Qianwan Terminal, Port of Qingdao, China. All port photographs shown throughout this article share this source and are reproduced with written permission for journal publication. Detection overlays, annotations, and heatmaps were generated in this study. MG-CTI: Mask-guided cross-task interaction; STFF: scale-tuned feature fusion; Conv: convolution; BBox: bounding box; BN: batch normalization; Cls: classification; SiLU: sigmoid linear unit.

Intelligence & Robotics
ISSN 2770-3541 (Online)

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/